Towards a Systemic Approach to Knowledge Integration in Learning Health Ecosystems: AI and DLT Perspectives

Nabil Georges Badr

2025

Abstract

A Learning Health System (LHS) is an essential paradigm for addressing the evolving complexities of healthcare systems, fostering continuous improvement, adaptability, and stakeholder collaboration. By integrating knowledge management with technological advancements, LHS enhances data-driven decision-making and the responsiveness of healthcare interventions. Artificial Intelligence (AI) has emerged as a powerful tool within Learning Health Systems, yet its evolving nature presents challenges related to ethical, traceable, and trustworthy data management. Distributed Ledger Technology (DLT) offers immutable and transparent data governance, yet its full potential remains unrealized due to the absence of integrated frameworks that could reinforce accountability and reliability in AI-driven processes. Addressing this gap is critical for developing robust, ethical, and efficient healthcare solutions. This paper examines the synergistic potential of AI and DLT within LHS, proposing a framework that leverages systematic knowledge integration, predictive analytics, and proactive interventions. By harnessing AI-driven automation, IoT-enabled data collection, and the secure, decentralized architecture of DLT, LHS can advance evidence-based healthcare, mitigate disparities, and promote equitable access to high-quality care.

Paper Citation

in Harvard Style

Badr N. (2025). Towards a Systemic Approach to Knowledge Integration in Learning Health Ecosystems: AI and DLT Perspectives. In Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KMIS; ISBN 978-989-758-769-6, SciTePress, pages 332-339. DOI: 10.5220/0013657100004000

in Bibtex Style

@conference{kmis25,
author={Nabil Badr},
title={Towards a Systemic Approach to Knowledge Integration in Learning Health Ecosystems: AI and DLT Perspectives},
booktitle={Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KMIS},
year={2025},
pages={332-339},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013657100004000},
isbn={978-989-758-769-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KMIS
TI - Towards a Systemic Approach to Knowledge Integration in Learning Health Ecosystems: AI and DLT Perspectives
SN - 978-989-758-769-6
AU - Badr N.
PY - 2025
SP - 332
EP - 339
DO - 10.5220/0013657100004000
PB - SciTePress